Basic Principles of Synthetic Biology

Engineering Biology for Innovation

Magnus Stefansson, MBA, Ph.D.

Applied Biotechnology and Enterprise Program

2025-06-13

Course Overview

Today’s Learning Objectives:

  • Define synthetic biology and its core principles
  • Understand key engineering approaches in biology
  • Explore standardization and modularity concepts
  • Examine commercial applications and market potential
  • Discuss ethical considerations and future directions

What is Synthetic Biology?

  • Definition: Engineering approach to biology that applies engineering principles to biological systems

  • Goal: Design and construct new biological parts, devices, and systems

  • Approach: Redesign existing natural biological systems for useful purposes

  • Interdisciplinary field: Combines biology, engineering, computer science, and chemistry

  • Bottom-up construction: Building biological systems from well-characterized parts

Source: Nature Reviews Molecular Cell Biology (2016)

Historical Context and Key Milestones

Key Milestones:

  • 1970s: Recombinant DNA technology foundations

  • 2000: First synthetic genome (φX174 bacteriophage)

  • 2003: BioBricks and standardized parts concept

  • 2010: First synthetic bacterial genome (Mycoplasma mycoides)

  • 2016: Synthetic yeast chromosome project

  • 2020s: CRISPR integration and advanced gene circuits

Core Principle 1: Engineering Design Cycle

Traditional Engineering Approach:

  • Design: Specify system requirements
  • Build: Construct the system
  • Test: Measure performance
  • Learn: Analyze results and iterate

Applied to Biology:

  • Design: Define biological function
  • Build: Assemble genetic circuits
  • Test: Measure biological output
  • Learn: Optimize and redesign

Source: Nature Biotechnology (2018)

Core Principle 2: Standardization

  • BioBricks: Standardized biological parts with defined interfaces
  • RFC Standards: Request for Comments defining part specifications
  • Interchangeable components: Parts that work together predictably
  • Characterization: Quantitative description of part behavior
  • Registries: Databases of characterized biological parts

Source: iGEM Foundation, Registry of Standard Biological Parts

Core Principle 3: Modularity

Hierarchical Organization:

  • Parts: Basic functional units (promoters, genes, terminators)
  • Devices: Combinations of parts with specific functions
  • Systems: Multiple devices working together
  • Chassis: Host organisms containing the systems

AI-generated modular system diagram

Core Principle 4: Abstraction

  • Physical Layer: DNA sequences, proteins, metabolites
  • Device Layer: Functional units (sensors, actuators, logic gates)
  • System Layer: Complete biological programs
  • Application Layer: Real-world functions and purposes
  • Benefit: Enables specialists to work at different levels without understanding all details

Source: Molecular Systems Biology (2017)

Genetic Circuits and Logic Gates

Boolean Logic in Biology:

  • AND gates: Multiple inputs required
  • OR gates: Any input sufficient
  • NOT gates: Inverter circuits
  • Toggle switches: Bistable systems
  • Oscillators: Periodic behavior

Applications:

  • Biosensors for environmental monitoring
  • Therapeutic circuits in medicine
  • Metabolic pathway control
  • Cell fate determination

Source: Science (2013) - Genetic logic circuits

Chassis Organisms

  • Escherichia coli: Most common, well-characterized, fast growth
  • Saccharomyces cerevisiae: Eukaryotic system, post-translational modifications
  • Bacillus subtilis: Gram-positive, protein secretion capabilities
  • Pichia pastoris: High protein expression levels
  • Mammalian cells: Complex protein folding, human-compatible
  • Minimal cells: Reduced genomes for predictable behavior

AI-generated comparison of different chassis organisms

Synthetic Biology Toolbox

DNA Assembly Methods:

  • BioBrick assembly
  • Gibson assembly
  • Golden Gate assembly
  • SLIC (Sequence and Ligation Independent Cloning)
  • CPEC (Circular Polymerase Extension Cloning)

Characterization Tools:

  • Flow cytometry
  • Fluorescence microscopy
  • RNA sequencing
  • Proteomics
  • Metabolomics

Source: Nature Methods (2019)

CRISPR Integration in Synthetic Biology

  • Programmable gene editing: Precise DNA modifications
  • CRISPRa/CRISPRi: Activation and interference systems -Base editing: Single nucleotide changes without double-strand breaks
  • Prime editing: Precise insertions, deletions, and substitutions
  • Multiplexed editing: Simultaneous modification of multiple targets

Source: Nature Reviews Genetics (2020)

Metabolic Engineering Principles

Pathway Design Strategies:

  • Heterologous pathway expression: Introducing foreign pathways
  • Pathway optimization: Balancing enzyme levels
  • Cofactor engineering: Managing cellular resources
  • Compartmentalization: Organizing reactions spatially
  • Dynamic regulation: Responsive pathway control

AI-generated metabolic pathway diagram

Protein Design and Engineering

  • Directed evolution: Laboratory-based protein evolution
  • Rational design: Structure-based protein modification
  • De novo design: Creating proteins from scratch
  • Protein-protein interactions: Engineering binding specificity
  • Allosteric regulation: Designing responsive proteins

Source: Nature Chemical Biology (2018)

Biosafety and Containment

Physical Containment:

  • Laboratory biosafety levels

  • Specialized equipment and facilities

  • Training and protocols

  • Waste management procedures

Biological Containment:

  • Auxotrophic strains (nutrient dependencies)
  • Kill switches and terminator genes
  • Orthogonal biological systems
  • Genetic firewalls

AI-generated biosafety illustration

Commercial Example 1: Ginkgo Bioworks

Business Model:

  • “Organism company” - designs custom microbes
  • Automated strain engineering platform
  • Applications in pharmaceuticals, agriculture, food
  • Partnerships with major corporations
  • Valuation: $15+ billion (2021)

Key Technologies:

  • High-throughput DNA assembly
  • Automated testing and optimization
  • Machine learning for design
  • Standardized biological parts

Source: Ginkgo Bioworks company materials

Commercial Example 2: Synthetic Spider Silk

  • Companies: Bolt Threads, Spiber, Modern Meadow
  • Product: Recombinant spider silk proteins in microorganisms
  • Properties: Stronger than steel, biodegradable, lightweight
  • Applications: Textiles, medical devices, protective equipment
  • Market potential: $1.3 billion by 2027

Source: Nature Materials (2019)

Commercial Example 3: Biofuels and Chemicals

Zymergen (acquired by Ginkgo):

  • Microbial strain optimization
  • Machine learning-guided engineering
  • Focus on specialty chemicals

Amyris:

  • Synthetic artemisinin production
  • Renewable chemicals from sugar
  • Cosmetics and fragrance ingredients

AI-generated biofuel production flowchart

Commercial Example 4: Synthetic Biology in Medicine

  • CAR-T cell therapy: Engineered immune cells for cancer treatment
  • Biosynthetic insulin: Recombinant human insulin production
  • Synthetic antibiotics: Novel antimicrobial compounds
  • Personalized medicine: Tailored therapeutic approaches
  • Market size: $39 billion by 2027

Source: Nature Biotechnology (2020)

Commercial Example 5: Food and Agriculture

Applications:

  • Impossible Foods: Plant-based meat with synthetic heme
  • Perfect Day: Animal-free dairy proteins
  • Motif FoodWorks: Designer food ingredients
  • Crop enhancement: Improved yield and nutrition

Benefits:

  • Reduced environmental impact
  • Enhanced nutritional content
  • Novel flavors and textures
  • Sustainable production

AI-generated sustainable food production ::::::::::::::::::::::::::::::::::::::